1) grey scale gradient matrix
灰度梯度矩阵
1.
The 1-D grey scale gradient matrixes of a finite number of pixels distributed symmetrically on both sides of each edge point with each edge point as a spine point are combined into a 2-D grey scale gradient matrix.
以各边缘点为脊点,分别在其两侧对称求取有限数量像素的一维灰度梯度矩阵,并由此构建二维灰度梯度矩阵。
2) gray level-gradient co-occurrence matrix
灰度-梯度共生矩阵
1.
According to the characteristics of the timber surface defect,we present an automatic technique for thresholding of timber surface defect images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
根据木材表面缺陷图像的特点,提出了基于灰度-梯度共生矩阵模型和最大熵原理的木材缺陷图像自动阀值化技术。
2.
Entropy thresholding method is an automatic technique for thresholding of digital images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
它包括二维匹配滤波预处理以增强血管的灰度,以及用灰度-梯度共生矩阵的最大熵阈值化方法。
3) gray-grads conjugate matrix
灰度-梯度共轭矩阵
4) gray level-gradient cooccurrent matrix
灰度梯度共生矩阵
5) gray-gradient co-occurrence matrix
灰度-梯度共生矩阵
1.
The gray-gradient co-occurrence matrix of the text region is calculated,and the optimum thresholds of segmented grayscale and gradient are found quickly according to the objective function.
首先计算文本区域的灰度-梯度共生矩阵,并根据目标函数快速地找到分割的灰度和梯度最佳阈值;然后在此基础上提取特征向量,送入神经网络进行分类;最后根据颜色极性判断的结果,分割出字符。
6) gradient matrix
梯度矩阵
1.
In this paper,the concept of gradient matrix(F(X)) is presented,and an algorithm is constructed to solve the symmetric solution of the minimum Frobenius norm residual problem:min‖(A1XB1,A2XB2)-(C1,C2)‖.
该文提出了梯度矩阵(F(X))的概念,构造了一种迭代法求最小二乘问题min‖(A1XB1,A2XB2)-(C1,C2)‖的对称解。
补充资料：不共生
【不共生】
谓六根六尘和合名之为共。前云不自生，则是根不能生；又云不他生，则是尘不能生。根尘各各既不能生，根尘相共又焉得生，故名不共生。
谓六根六尘和合名之为共。前云不自生，则是根不能生；又云不他生，则是尘不能生。根尘各各既不能生，根尘相共又焉得生，故名不共生。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条